JRSS-A publishes research showing how statistics play a vital role in life and benefit society l #data l #statistics | #academic | #bayesian | #stochastic
Joined December 2020
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And for the π¦ Spotlight article:
π³ Ratzke, Krause & Sippel present "Unravelling a vicious cycle: extreme weather events, urban expansion, and deforestation" . #ClimateChange #Deforestation β doi.org/10.1093/jrsssa/qnag0β¦
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π The cycle doesn't look the same everywhere: strength and significance vary by continent and development level, pointing to the need for region-specific land use planning and multilevel governance to break it.
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This is the first global evidence for a feedback loop linking disaster damages, urban expansion, and deforestation β οΈπ³
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Late April & May highlights from JRSS-A! New original articles spanning surveys, economics, clinical trials & more. Thread π (1/8)
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π³οΈ Seo et al. bring β0-regularization to item response theory for robust ideal point estimation β cleaner political scaling with sparse, interpretable solutions. #PoliticalScience #IRT β doi.org/10.1093/jrsssa/qnag0β¦ (7/8)
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πΊοΈ Cabello et al. propose area-level Dirichlet mixed models for small area estimation of proportions and rates β a natural fit when your outcome lives on the unit interval. #SmallAreaEstimation #Bayesian β doi.org/10.1093/jrsssa/qnag0β¦ (8/8)
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Journal of the Royal Statistical Society: Series A retweeted
Discover the latest special issue from @JRSS_A: βBlockchains in Society,β showcasing research on blockchain analytics, digital assets, fraud detection, and cryptocurrency networks.
@RoyalStatSoc
Read the issue: oxford.ly/48gzHyB
ALT Special Issue:\u00A0Blockchains in Society\n
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Journal of the Royal Statistical Society: Series A retweeted
New article with @albertocaimo!
ββ Caimo & Gollini develop separable models for dynamic signed networks β where relationships can be positive, negative, or absent, and all three matter. #NetworkScience #SocialNetworks β doi.org/10.1093/jrsssa/qnag0β¦ (7/10)
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And in the spotlight, from HΓ₯vard Hungnes
"A novel multivariate composite estimator for the Labour Force Survey"
doi.org/10.1093/jrsssa/qnag0β¦
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The method explicitly models autocorrelated sampling errors and time-varying wave biases, offering a robust alternative to state-space models and models all labour market categories simultaneously.
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Applied to Norwegian LFS data, the new estimator provides substantial precision gains for estimates of change over time in employment.
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𧡠April (and late March) highlights from JRSS-A! New original articles spanning networks, crime, genomics, finance & more. Thread π (1/10)
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π¨ Lee et al. model crime on linear networks (roads, paths) using a spatio-temporal Dirichlet process mixture β because crime doesn't happen in open space. #CrimeMapping #BayesianNonparametrics β doi.org/10.1093/jrsssa/qnag0β¦ (9/10)
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πΆHoffman & Block model emergent structures in human mobility β connecting individual movement decisions to macro-level patterns. #Mobility #NetworkScience β doi.org/10.1093/jrsssa/qnag0β¦ (10/10)
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